The Decision Rain Library Project is deliberately small and opinionated, but it is not meant to run unchanged out of the box. The tag families, example entries, and fit judgments in this template reflect a starting point — not a finished personal system. Before you use this seriously, you should adapt it so that the tags describe your actual environment, the domains reflect the topics you care about, and the examples mirror the kinds of links you actually save.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/XxYouDeaDPunKxX/decision-rain-library-project/llms.txt
Use this file to discover all available pages before exploring further.
The Five Customization Areas
Each area below corresponds to a concrete part of the template. Start with the ones that feel most wrong for your situation.Fit Tags
Define what tools, accounts, devices, budget constraints, and setup friction thresholds are real for your environment. The built-in fit tags are a reasonable default, but your stack may differ.
Domains
The
domain/* family captures the topic or subject area of a saved link. Add values for the domains you work in — automation, writing, design, hardware, research, productivity, or anything else that matters to your workflow.Item Types
The
type/* family describes what kind of object a link is: repo, guide, paper, service, directory, pattern, tutorial, or idea. Extend this list only if a real gap appears in your actual saved links.Priority Markers
The
priority/* family contains a single built-in value: priority/high. This is an operator attention marker — it does not replace status/* or next/*. Add new priority values only if your workflow genuinely needs them and you have operator approval.Golden Examples
The
docs/05_EXAMPLES_GOLDEN.md file contains synthetic examples designed to prevent taxonomy drift. Replace them with real entries from your own reviewed links so the AI assistant has examples that match your actual decisions, not generic ones.The Core Rule: Tags Help You Find and Decide Later
The simplest test for any tag is this: will it help you find this entry later, or help you make a better decision when you return to it? Tags are not expressive labels, sentiment signals, or notes to yourself about how you felt when you saved the link. They are a controlled vocabulary for retrieval and judgment. This rule applies to every family — fit, domain, type, status, truth, risk, and next.Good Tags vs. Bad Tags
The difference between useful tags and noisy tags is specificity and interrogability. A useful tag can be queried with intent. A vague tag can only be filtered out.Governance: Unauthorized Tag Creation Is Not Allowed
The tag taxonomy is a controlled grammar. Every value in every family exists because a human operator approved it. The AI assistant is not permitted to grow the taxonomy on its own. The approved families are:When to Add New Tags
A tag gap is not a failure — it is useful information. If an entry genuinely cannot be described by any existing tag value, the correct response is:Identify the gap
The AI reports which family is missing a value and explains why no existing value fits the entry.
Propose the smallest addition
The AI proposes the most minimal new tag that fills the gap — one value, not a new family or a set of synonyms.
Wait for approval
The AI does not use the proposed tag until the operator explicitly approves it. Silence is not approval. Prior similar approval is not approval.